Appraising Success of LLM-based Dialogue Agents
Author:
Affiliation:
1. Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM),New Delhi,India
2. Indraprastha Institute of Information Technology (IIIT), Delhi,Dept. of Computer Sc. and Engineering,New Delhi,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10498128/10498148/10498880.pdf?arnumber=10498880
Reference24 articles.
1. Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation With Large Language Models
2. Challenges and Applications of Large Language Models;Kaddour,2023
3. A Very Gentle Introduction to Large Language Models without the Hype by Mark Riedl Medium,2024
4. Large Language Models Are Semi-Parametric Reinforcement Learning Agents;Zhang,2023
5. Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk;Ulmer,2024
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